Mining social media for ultraviolet light exposure analysis

ABSTRACT

Social media databases are minded for data related to a subject person. The data in indicative of a level of ultraviolet light exposure of the subject person. An ultraviolet violet exposure profile for the subject person is generated based upon the data and a health assessment report provided. The data may include timestamped images of the subject person and other related persons. The skin characteristics within images are analysed to determine an ultraviolet light exposure level for the subject person from each image. The skin characteristics may include skin colour, freckling and blemishing. The ultraviolet light exposure profile may be developed over an extended interval based upon the image timestamps. The health report may be used to mitigate risks, such as skin cancer, associated with exposure to ultraviolet light.

BACKGROUND

This disclosure broadly relates to the field of determining levels ofexposure of an individual to ultraviolet light, and more particularly tothe field of analysing social media data to determine such levels ofexposure.

Skin cancer is a cancer that forms in the tissues of the skin when skincells are damaged, including by overexposure to ultraviolet light fromthe sun. There are three main types of skin cancer, named after the typeof skin cell from which they arise: melanoma, which forms inmelanocytes, the skin cells that make pigment; basal cell carcinoma,which forms in the lower part of the epidermis, the outer layer of theskin; and squamous cell carcinoma, which forms in squamous cells, theflat cells that form the surface of the skin. Of these three, melanomais the least common skin cancer, but also is the most aggressive, themost likely to spread and, if left untreated, fatal. Sun exposure is asignificant risk factor for all three types of skin cancer. There aremany other risk factors, including personal and family histories; skinand hair colour; and even eye colour. Other risk factors include molesand immune system strength.

Skin cancer is the most common of all cancers, accounting for nearlyhalf of all cancers in the United States; more than 3.5 million skincancers are diagnosed annually in more than 2 million people, withmelanoma accounting for more than 75,000 cases and over 8,500 deaths.About one in five Americans will develop skin cancer in their lifetime,and about one in 50 Americans will develop melanoma in their lifetime.Skin cancer is also not limited to the elderly: melanoma is the mostcommon form of cancer for young adults 25-29 years old and the secondmost common form of cancer for adolescents and young adults 15-29 yearsold. One person dies of melanoma every 57 minutes. Skin cancer alsoaccounts for many billions of dollars in both direct and indirectspending. In the United States, according to the National CancerInstitute, the total direct costs associated with the treatment fornon-melanoma skin cancer in 2004 was $1.5 billion, and the estimatedtotal direct cost associated with the treatment of melanoma in 2010 was$2.36 billion.

Exposure to ultraviolet light from the sun can not only result in skincancer but also can result in changes in skin characteristics such asskin colour or tan, freckling, and skin blemishes. Such changes areoften recorded in images that may be stored on social media databases orweb sites. Such databases are able to accumulate numerous images over anextended period of time. Analysis of an ultraviolet light exposureprofile may be beneficial in mitigating harm caused by exposure toultraviolet light exposure.

SUMMARY

A method comprises receiving a multiplicity of images from an at leastone remote database; analysing the multiplicity of images to determinean ultraviolet light exposure profile of a subject person; andgenerating a health assessment report for the subject person based uponthe ultraviolet light exposure profile.

A computer storage program product comprises a storage medium readableby a processing circuit and storing instructions for execution by theprocessing circuit configured to perform a method comprising: receivinga multiplicity of images from an at least one remote database; analysingthe multiplicity of images to determine an ultraviolet light exposureprofile of a subject person; and generating a health assessment reportfor the subject person based upon the ultraviolet light exposureprofile.

A device comprises a data receiver configured to receive a multiplicityof images recorded with visible light, the multiplicity of imagesreceived from a plurality of social media databases; a subject personidentifier configured to analyse the multiplicity of images to identifya plurality of subject person images including a subject person having askin colour that varies with exposure to ultraviolet light; a skincolour determiner configured to determine a skin colour of the subjectperson within each of the subject person images; an ultraviolet lightexposure determiner configured to generate a multiplicity of data pointscorresponding to the multiplicity of images, each data pointcorresponding to an ultraviolet light exposure level for each of thesubject person images determined based upon the skin colour of thesubject person within each of the subject person images; a multiplephoto analyser configured to generate an ultraviolet light exposureprofile for the subject person based upon the multiplicity of datapoints; and a report generator configured to generate a healthassessment report for the subject person based upon the ultravioletlight exposure profile, the health assessment report including anultraviolet light exposure risk assessment for the subject person.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, and which together with the detailed description below areincorporated in and form part of the specification, serve to furtherillustrate various embodiments and to explain various principles andadvantages all in accordance with the present disclosure, in which:

FIG. 1 illustrates a system in which a device generates a report basedupon a subject person's exposure to ultraviolet light, the ultravioletlight exposure being based upon data received from multiple social mediadatabases;

FIG. 2, FIG. 3, FIG. 4 and FIG. 5 illustrate examples of skin colour ofimages of a subject person based upon exposure to ultraviolet light;

FIG. 6 illustrates an example of a chart for determining hours per dayof ultraviolet light exposure based upon skin colour of a subject personincluded within a recorded image;

FIG. 7 and FIG. 8 illustrate an example of a social media image that maybe used in another method for determining ultraviolet light exposurelevels based upon skin colour;

FIG. 9 and FIG. 10 illustrate an example of a social media image thatmay be used in another method for determining ultraviolet light exposurelevels based upon freckling;

FIG. 11 illustrates an example of a graph of an ultraviolet lightexposure profile of a subject person. The graph shows twelve data pointsover a period of two years;

FIG. 12 illustrates an example of a representative flow diagram of aprocess for generating a health assessment report for a subject personbased upon an ultraviolet light exposure profile analysed from amultiplicity of data points received from social media databases;

FIG. 13 illustrates an example of a representative flow diagram of aprocess for determining ultraviolet light exposure of a subject personfrom an image; and

FIG. 14 illustrates an example of a representative flow diagram of aprocess for determining ultraviolet light exposure by analysing skincolour of an image.

DETAILED DESCRIPTION

In the following discussion, details are provided to help thoroughlyunderstand the present disclosure. However, it is apparent to those ofordinary skill in the art that even though there may be no such details,the understanding of the present disclosure would not be influenced. Inaddition, it should be further appreciated that any specific terms orapplications used herein are only for the convenience of description,and thus the present disclosure should not be limited to only use in anyspecific terms or applications represented and/or implied by such terms.

Generally speaking, images and image metadata posted on social mediadatabases including other online image galleries are analysed to trackchanges over time of hair colour, and skin colour, skin tone, blemishesand lesions to produce a health assessment report which may allow forestimates of the risk of development of skin diseases includingmelanoma, basal cell carcinoma and squamous cell carcinoma. A model ofultraviolet light exposure, based upon the images is related to the riskof development of these skin diseases. The health assessment report maybe used to predict general aspects of a person's lifestyle. Also,ultraviolet light exposure and lifestyle attributes may be implied orinferred based upon the ultraviolet light exposure and lifestyleattributes of linked or related individuals within social networks.

People have used their private social circles to share images ofthemselves and others for decades. With the recent proliferation ofsocial networking sites, such as Facebook.com, Twitter.com, weibo.com,renren.com, and the advent of consumer cameras able to easily uploadrecorded images to the social networking sites, the sharing of pictureshas become easier and more common. In addition to the images themselves,people also share significant metadata, including timestamps andlocation data, attached to those images, e.g. in image descriptions onFacebook or in tweets on Twitter. Most of these social networking sitesalso have the capability to tag or label others in their network. Thisfeature enables tracking of the changes people undergo by collecting theimages of a person and analysing changes over time of hair colour, andskin colour, tone, blemishes and lesions. As a simplified description,the processes involves mining social media sites to collect pictures ofa subject person under analysis/search, generating a colour segmentedimage with timestamps information obtained from the metadata, analysingthe colour segmented images and build a ultraviolet light exposureprofile of a subject person over time, analysing the colour segmentedimages and build a ultraviolet light exposure profile of the peoplerelated to the subject person under analysis, and building a relativeultraviolet light exposure profile of the subject and associated people.

Mining social media sites to collect pictures of a subject underanalysis/search includes a search of image data that are tagged with thesubject's information (name, nick name, address, workgroup, fun group,etc.) within social networking sites. The search task can be performedusing the links the subject has with their friends and relatives, asdone by Facebook and Twitter when searching for known circle of friends.Generating a colour segmented image with timestamps information obtainedfrom the metadata (e.g., the date the image was tagged or uploaded)involves creating segmented images of the search results, where thesegmentation is primarily done on colour and tone. For example, a tannedperson could be relatively darker in the images taken during summertimes as compared to when the person was indoors during colder seasons.This step also involves collecting metadata of the images, such as thetime and place the image was taken, and associating the images with themetadata. The processes includes analysing the colour segmented imagesand building an ultraviolet light exposure profile of a person over timeinvolves the process of image analysis, where the colour segmentedimages are sorted in time (e.g, summer, winter) and space (e.g, beach,indoors, parties, etc.) and a ultraviolet light exposure profile isbuilt. The ultraviolet profile clearly helps describe when, where, how,and to what extent the person changed their skin colour and tone as aresult of ultraviolet light exposure. Analysing the colour segmentedimages and building a ultraviolet light exposure profile of the peoplerelated to the subject person under analysis involves the process ofinferring, based upon both image analysis and social links, theultraviolet light exposure profile of people related to or otherwiselinked to the subject person. For instance, a couple holidaying aroundbeaches could potentially have the same ultraviolet light exposureprofile during the holiday time, although only one of them posted theirimage to the social media. The posted images may or may not have thesubject person within them. Building a relative ultraviolet lightexposure profile of the subject and related people analyses people whoare not in the pictures, but are related to the subject under analysis.This relationship could be a permanent one (e.g., marriage), seasonal(e.g., holiday friends), or other social links that are determined byonline social interactions. Then, the ultraviolet light exposure levelof the related person can be applied to the subject person.

The images of the present description are primarily recorded withvisible light. An image recorded with visible light includes imagesrecorded from light in the visible light spectrum and excludes imagescaptured primarily with ultraviolet light and images captured primarilywith infrared light. An image recorded with visible light include imagescaptured with ambient light, sunlight and flash photography. An imagerecorded with visible light is intended to have subject matter thatappears substantially identical to a scene perceived by an observerhaving viewed the subject matter when the image was recorded.

A related person has an identifiable relationship with the subjectperson wherein the ultraviolet light exposure of the subject person maybe synthesized from the determined ultraviolet light exposure of therelated person. In one example the related person may be a relative ofthe subject person, such as the spouse, parent, child or sibling. Inanother example, the related person may be included in an image recordedby the subject person. In another example, the related person may beknown to spend time with the subject person, such as team mates ortravel companions. The relationship may be predetermined and designatedby the subject person or may be determined from metadata included withthe images, the metadata indicative of the relationship.

FIG. 1 illustrates a system in which a device generates a report inbased upon a subject person′ exposure to ultraviolet light, theultraviolet light exposure being based upon data received from multiplesocial media databases. During event 110, a subject person 100 isincluded in a recorded image 112 taken by a first camera operator 114operating a first camera 116. The first camera 116 may, in this example,be a “point-and-shoot” pocket camera. Data associated with event 110 isstored on first social media database 118, which in one example may be asocial media database such as the database maintained by the Facebooksocial media service. Event 110 may occur at a first time during a firstseason, for example the season may be winter and the time may beFebruary 14. The data associated with the event includes informationfrom which the subject person's exposure to ultraviolet light may bedetermined. Such data may include the image 112 recorded by the camera116 and may include the skin colour or amount of tan of the subjectperson. In another example, the data may include information which maybe indicative of a level of ultraviolet light exposure. For example thedata may include a message indicating that the subject person has beenindoors for an extended period because of inclement winter weather:accordingly, it may be determined that the subject person has receivedalmost no ultraviolet light exposure.

During event 120, the subject person 100 is included in a recorded image122 taken by a second camera operator 124 operating a second camera 126.The second camera may, in this example, be a digital signal lens reflex(DSLR) camera recording images using natural lighting or other form ofvisible light illumination. Data associated with event 120 may be storedon a second social media database 128, which in one example may be asocial media database such as the database maintained by the Googlesocial media service. Event 120 may occur at a second time during asecond season, for example the season may be spring and the time may beApril 1. The data associated with the event includes information fromwhich the subject person's exposure to ultraviolet light may bedetermined. Such data may include the image 122 recorded by the camera126 and may include the skin colour or amount of tan of the subjectperson at the time of the image recording. The data may includeinformation which may be indicative of a level of ultraviolet lightexposure. For example the data may include a message indicating that thesubject person is enjoying spending lunches in the sunlight:accordingly, this additional information may be used to determine thatthe subject person is receiving regular exposure to ultraviolet light.

During event 130, the subject person 100 is recording an image 132 of arelated person 134 taken by a third camera 136. The third camera may, inthis example, be a cell phone camera belonging to or otherwiseassociated with the subject person 100. Data associated with event 130may be stored on a third social media database 138, which in oneexample, may be a social media database such as the database maintainedby the MySpace social media service. Event 130 may occur at a third timeduring a third season, for example the season may be summer and the timemay be July 4. The data associated with the event includes informationfrom which the subject person's exposure to ultraviolet light may bedetermined. Such data may include the image 132 recorded by the camera136 and may include the skin colour or amount of tan of the relatedperson at the time of the image recording. In one example, the data mayinclude an image of a foot of the subject person with sandals removedafter a day in the sun. Sandals block portions of the skin fromultraviolet light exposure and thus have a different skin colour thanareas of the skin which have received ultraviolet light exposure. Thedata may include information which may indicate that the person in thephoto is related to the subject person and thus the determined level ofultraviolet light exposure of the related person may be applied to thesubject person. The relationship between the subject person and therelated person may be determined in any of a number of ways. Forexample, image 132 was recorded with the cell phone camera of thesubject person, and thus the relationship may be established. In anotherexample, the metadata associated with image may indicate therelationship, for example the image may include information identifyingthe person in the image as a spouse or companion of the subject person,or may include a message indicating that the subject person has spentthe day with the person in the image. Thus, the data associated withevent 130 includes information indicative of a level of ultravioletlight exposure of the subject person. For example the data may include amessage indicating that the subject person is associated with therelated person even though the subject person is not included in animage associated with event 130.

Cameras 116, 126 and 136 may be typical cameras used to capture amultiplicity of images recorded primarily with visible light, such thatthe recorded image appears substantially the same as the image viewed bythe unaided eye when the image was recorded using light primarily in thevisible spectrum. One intended purpose of recording each image is toallow those accessing the social media databases to share in theexperience of the events from which the images were recorded while alsobuilding an ultraviolet light exposure of a subject person. Thisintended purpose has nothing to do with the analysis of ultravioletlight exposure levels of the subject person. Thus, the camera andlighting of the recorded images do not unduly skew the recorded imagestowards the ultraviolet or infrared spectrums. Such skewing may requirespecialized cameras and lighting and may produce images that appearsubstantially different from the appearance of the event as seen by theunaided eye when the event is illuminated primarily with visible light,and would detract from an intended purpose of the recording of theimages. Furthermore, requiring use of such specialized cameras andlighting skewed towards the ultraviolet or infrared spectrum maysignificantly reduce the availability of images of the subject personavailable on social media databases, thereby hampering the amount ofavailable data and long term analysis of ultraviolet light exposure ofthe subject person. Furthermore, the dissimilarity of the image recordedwith light primarily above or below the visible spectrum distorts theappearance of the persons in the image in a way that tends to detractfrom the use of the image for social media communications.

Social media databases 118, 128 and 138 include a plurality of socialmedia databases that are remote databases that are not necessarilyhosted by device 150. The remote databases may be included in a cloud140 which may be accessed by device 150 through the internet or othernetwork for receiving data and images 112, 122, 132 from events 110,120, and 130. Images 112 and 122 comprise a plurality of subject personimages including a subject person having a skin colour that varies withexposure to ultraviolet light. Image 132 include a related person image.The social media databases may also be accessed by device 150 using theinternet or other network to access the cloud 140. In one example, theimages may be stored on a single social media database. In anotherexample, several social media databases may include several images orother data indicative of an ultraviolet light exposure level of thesubject person.

Device 150 corresponds to a digital processing machine and includes acomputerized device able to access the cloud 140 and data stored onremote social media databases 118, 128 and 138. The computerized devicemay include any of a number of different devices including a server, adesktop computer, a laptop computer, a tablet, and a cellphone. Device150 includes a social media data receiver 152 that receives dataincluding images and metadata from at least one remote social mediadatabase. The data is then analysed by subject person identifier 154 todetermine if any of the data identifies the subject person. The analysismay include examining the data for names and other data segments such asphone numbers used to identify the subject person. If the data includesimages such as a photograph or a video recording, then facialrecognition may be employed to identify if the subject person isincluded in the image. Also, metadata associated with the image may beanalysed to identify the subject person. Other methods of determining ifdata is to be associated with the subject person include determining ifthe data comes from an account assigned to the subject person, or froman account of a person related to the subject person, such as a spouse,partner or companion of the subject person. Other methods of determiningif data is associated with the subject person or identifies the subjectperson may be implemented while remaining within the scope of thisdescription.

If the data includes an image, be it a photograph, video recording orother image recorded primarily with visible light, then the colour ofthe skin of the subject person or person related to the subject personis determined by skin colour determiner 156. This may be done byselecting an area of skin exposed to sunlight and determining its colourby analysing the area using colour segmentation. For example, if theface of the subject person or related person is to be analysed, the areaof skin exposed to sunlight could be the forehead area of the face, orthe darkest area of skin of the face. One example of colour segmentationknown to those familiar with the art includes decomposing the imagesinto red, green and blue (RGB) components, another example incudes hue,saturation and lightness (HSL). Other processes such as white balance orother compensation methods may also be employed to account for differentlighting, camera settings, and image capturing phenomena known to thosefamiliar with the art, to obtain a more consistent colour segmentationdetermination from image to image.

Ultraviolet light exposure determiner 158 determines an amount ofultraviolet light exposure of a person from data received from a socialmedia database and a corresponding data point corresponding to theultraviolet light exposure level. If the data is from the skin colour ofan image, then the ultraviolet light exposure may be determined from theskin colour in any of several ways. In one example, a known relationshipbetween skin colour and average ultraviolet light exposure isestablished based upon prior determinations or attributes of the personrecorded in the image. In another example, skin colour of an area ofskin exposed to ultraviolet light is compared to a skin colour of anunexposed area of skin that has been less exposed to ultraviolet lightof the person. In one example the exposed and unexposed areas of skinmay be in a single image, in another example, the exposed and unexposedareas of skin may be in different images recorded at different times:for example, an unexposed area may be recorded in winter where theperson spends significant time indoors free of ultraviolet lightexposure and the exposed area may be recorded in summer where the personspends significant time outdoors and receives exposure to ultravioletlight.

The ultraviolet light exposure determiner may also analyse social mediadata to qualify its determination based upon the behavior of the subjectperson. For example, if the data indicates the person has received achemical tan, a chemical spray, or a “spray tan” of chemicals thatcolour the skin to provide the appearance of a tan received byultraviolet light exposure, then the ultraviolet light exposuredetermination made by image processing may be modified, reduced,discounted, given less weight or even eliminated. If the data indicatesthe person has visited a tanning booth during winter, thereby receivingexposure to ultraviolet light without being exposed to sunlight, thenany unexposed determination may be accordingly discounted or given lessweight. Other behaviors include a spending a time at a vacationlocation, participation in an outdoor sport, visiting ultraviolettanning salon, all of which have characteristic ultraviolet lightexposure attributes which may be used to qualify the ultraviolet lightexposure determination. Ultraviolet light exposure determiner 158 mayalso determine ultraviolet light exposure even if the data does notinclude a recorded image. For example if the data is a calendarappointment indicating the person will spend two hours surfing on acertain beach at a certain time, then exposure to ultraviolet lightdetermination may be made accordingly. Furthermore, ultraviolet lightexposure by sunlight may vary depending upon the weather, thus theweather report and other atmospheric conditions for the beach at thetime may be analysed to determine the level of ultraviolet lightreceived from the sun by the during the calendar appointment.

Multiple photo analyser 160 then analyses a multiplicity of photos overa time span to determine an ultraviolet light exposure profile of thesubject person based upon the data points determined by the ultravioletlight exposure determiner 158. Since the social media databasesaccumulate images and other data related to the subject person, theimages captured by the subject person and as well as others, over manyyears, the data may be mined to obtain a long term determination of theultraviolet light exposure profile of the subject person. Thus, what isshown is an example of analysing, by a digital processing machine, themultiplicity of images to transform the multiplicity of images into anultraviolet light exposure profile of a subject person. Report and alertgenerator 162 then generates a report based upon the profile and mayalso generate an alert if the profile shows a developing health risk.The report and/or alert may be provided to the subject person, a personrelated to the subject person or a doctor or attending physician to beused in counseling the subject person on health related matters. Thehealth assessment report includes an ultraviolet light exposure riskassessment for the subject person. The health assessment report mayinclude a risk related to skin cancers and other skin maladies, as wellas advice for mitigating the risk.

FIG. 2, FIG. 3, FIG. 4 and FIG. 5 show examples of skin colour of imagesof a subject person based upon exposure to ultraviolet light. The imagesare recorded over a period of time and may be mined from one or moresocial media databases. For example, the image of FIG. 2 may have beenrecorded in winter where the subject person spent most of the timeindoors, not exposed to ultraviolet light from the sun; the image ofFIG. 3 may have been recorded in spring where the subject person spentsome time in the sun, received some exposure to ultraviolet light; theimage of FIG. 4 may have been recorded in late summer where the subjectperson spent more time in the sun, receiving more exposure toultraviolet light; and the image of FIG. 5 may have been recorded inmidsummer after a day where the subject person spent a long amount oftime in the sun, receiving excessive exposure to ultraviolet lightresulting in a sunburn.

To provide examples of skin colour of recorded images, a red green blue(RGB) colour scale is used to segment the image into colours. The scalefor each colour spans from 0 to 255 with an RGB of (0, 0, 0)corresponding to black and an RGB of (255, 255, 255) corresponding towhite. Using this scale, the RGB colour of the portion of the image ofFIG. 2 including the skin colour of the subject person may be (255, 245,235). This RGB colour corresponds to the subject person having skin witha light colour, the light colour being indicative of little or no suntan. In this example, based upon the attributes of the subject person,it may be determined that the subject person has less than or equal toone half an hour per day of exposure to ultraviolet light based upon theimage of FIG. 2.

The RGB colour of the portion of the image of FIG. 3 including the skincolour of the subject person may be (240, 175, 150). This RGB colourcorresponds to the subject person having skin with a medium colour, themedium colour being indicative of some sun tan. In this example, basedupon the attributes of the subject person, it may be determined that thesubject person has two hours per day of exposure to ultraviolet lightbased upon the image of FIG. 3.

The RGB colour of the portion of the image of FIG. 4 including the skincolour of the subject person may be (160, 80, 40). This RGB colourcorresponds to the subject person having skin with a dark colour, thedark colour being indicative of a developed sun tan. In this example,based upon the attributes of the subject person, it may be determinedthat the subject person has four hours per day of exposure toultraviolet light based upon the image of FIG. 4.

The RGB colour of the portion of the image of FIG. 5 including the skincolour of the subject person may be (255, 175, 150). This RGB colourcorresponds to the subject person having skin with a red colour, the redcolour being indicative of a sunburn. In this example, based upon theattributes of the subject person, it may be determined that the subjectperson has eight hours per day of exposure to ultraviolet light basedupon the image of FIG. 5.

FIG. 6 shows an example of a chart for determining hours per day ofultraviolet light exposure based upon skin colour of a subject personincluded within a recorded image. An image of the subject person showinga light, medium, dark and red skin colours, having RGB values of (255,245, 235), (240, 175, 150), (160, 80, 40), and (255, 175, 150)respectively, corresponds to 0.5, 2.0, 4.0 and 8.0 hours per day ofultraviolet light exposure, respectively. The chart of FIG. 6 is for aparticular subject person, other persons may have other charts forrelating skin colour to levels of ultraviolet light exposure. The chartmay be obtained empirically by monitoring the skin colour of the subjectperson based upon known levels of ultraviolet light exposure, or thechart may be determined from attributes of the subject person.Attributes of the subject person that may be useful in determining therelationship between skin colour and a level of ultraviolet lightexposure include age, gender, hair colour, eye colour, skin type (seethe Fitzpatrick scale for example which is known to those familiar withthe art), and geographic origin (see the Von Luschan chromatic scale forexample which is known to those familiar with the art).

FIG. 7 and FIG. 8 illustrate an example of a social media image that maybe used in another method for determining ultraviolet light exposurelevels based upon skin colour. The image of FIG. 7 shows a foot 700 ofthe subject person, wherein the subject person is wearing a sandal 710.FIG. 8 shows an image of the foot 700 of the subject person after thesandal is removed. FIG. 8 shows an image of the subject person having anexposed area of skin 820 having exposure to ultraviolet light because itwas not covered by the sandal, and an unexposed area of skin 830 havingless exposure to ultraviolet light than the exposed area of skin. Inthis example the colour of the unexposed area may have an RGB value of(255, 245, 235) and the colour of the exposed area may have an RGB valueof (240, 175, 150). The unexposed area 830 may indeed have some exposureto ultraviolet light, albeit less exposure than the exposed area 820.Based upon the colour difference it may be determined that the subjectperson has spent about 2 hours per day being exposed to ultravioletlight. This determination may be arrived at using a chart that showsthat an unexposed skin colour of (255, 245, 235) provides acharacteristic relationship between hours per day of exposure toultraviolet light and skin colour, which in this example happens tocorrespond to the chart of FIG. 6. Note that an unexposed skin colourthat is different from the colour of area 830 (255, 245, 235) may resultin a different relationship between skin colour and hours per day ofexposure to ultraviolet light. Thus, in another example, a chartdifferent from the chart of FIG. 6 may be used to determine therelationship between skin colour and ultraviolet light exposure.

One potential advantage of the approach of processing the image of FIG.8 is that the individual attributes of the person in the image, such asage, gender, hair colour, eye colour, skin type, and geographic originneed not be known. Thus, if the subject person is known to be related tothe person in the image, then the ultraviolet light exposure of theperson in the image may be either applied or indirectly equated to theultraviolet light exposure of the subject person even though the subjectperson may not be included in the image. For example, if the person inthe image is known to be a traveling companion of the subject person andthe determination made that the person in the image received two hoursper day of exposure to ultraviolet light, then the two hours per day ofultraviolet light exposure may be equated to the subject person basedupon the assumption that the subject person and the companionparticipated in similar activities during their travels. This indirectdata may be useful where more direct data relevant to the exposure ofthe subject person to ultraviolet light, such as the analysis of a photoof the subject person, is not available or can be used as supplementaldata and may be assigned a lesser weight than an ultraviolet lightexposure level determined from an image including the subject person.The relationship between the related person in the image and the subjectperson may be established in any of a number of ways including data fromthe social media database associated with the image that indicates thatthe person in the image is a travel companion of the subject person. Forexample, metadata may indicate that the image of FIG. 8 was recordedwith a camera belonging to the subject person and the image data mayhave a caption such as “my companion's foot tan”. The caption indicatesthe relationship with the subject person.

FIG. 9 and FIG. 10 illustrate an example of a social media image thatmay be used in another method for determining ultraviolet light exposurelevels based upon freckling. Freckling increases as a person's exposureto ultraviolet light increases. FIG. 9 and FIG. 10 represent an image ofthe same person taken at different times. The image of the personrecorded in FIG. 9 has less freckling than the image of the personrecorded in FIG. 10. Thus, the person at the time of recording to FIG.10 has received more average exposure to ultraviolet light than at thetime of recording of FIG. 9. Such an analysis may be used inestablishing an ultraviolet light exposure profile of the subjectperson. Furthermore, other visible characteristics of a person changewith ultraviolet light exposure including hair colour and skinblemishes. In certain persons, hair colour tends to lighten withexposure to ultraviolet light. In certain persons, skin blemishes tendto increase with exposure to ultraviolet light. These changingcharacteristics may be used in determining an ultraviolet light exposureprofile of a subject person. Similar to the analysis of skin colour andultraviolet light exposure rates, the personal attributes of the personrecorded in the image may be used in determining the ultraviolet lightexposure rate based upon changes in freckling, hair colour and skinblemishes.

FIG. 11 illustrates an example of a graph of an ultraviolet lightexposure profile of a subject person. The graph shows twelve data pointsover a period of two years. The data points may be determined from dataincluding images and metadata received from social media databases. Eachdata point represents a determined level of ultraviolet light exposurebased upon data from events received from at least one social mediadatabase. In other examples, there may be significantly more (or less)data points accumulated over a significantly longer (or shorter) periodof time and the data points may have an associated weight based upon thedata received from the remote database. Line 1100 shows the ultravioletlight exposure profile of the subject person over the term of the graph.In this example, the line assumes that each data point is given the sameweight and a smoothed line drawn between the data points. In otherexamples, where data points may be given varying weights, a line drawnbetween weighted data points using statistical analysis in a mannerknown to those familiar with the art. In one example, a data pointdetermined from a high resolution image of the subject person with agood white balance calibration may be given greater weight than a datapoint determined from low resolution image of a related person with nowhite balance. The lower weight results from either the resolution ofthe image being poor, or the image may not include a significant whitearea in which to accurately calibrate the RGB colour segmentation, orthat the related person may have a different level of ultraviolet lightexposure than the exposure determined for the related person at the datapoint.

In the example of FIG. 11, for a subject person having the attributescorresponding to the attributes of the subject person in the chart ofFIG. 6, it has been determined that an average annual ultraviolet lightexposure profile of less than two hours per day provides a lowultraviolet light exposure risk, as indicated by line 1110, while anaverage annual ultraviolet light exposure profile of more than fourhours per day provides a high ultraviolet light exposure risk, asindicated by line 1120. Line 1120 is a graphical representation of anaverage exposure of ultraviolet light for the first year of the graphbased upon the data points 1-6. The average is less than two hours perday and the ultraviolet light exposure risk is low. The healthassessment report would then show that in the first year of theassessment the ultraviolet risk was low. However, image event 4 resultedin a determined exposure beyond two hours per day resulting in adetermined medium risk for the subject person. If the social media datawas analysed at a point in time close to the occurrence of data point 4,then in response an alert could be generated by the health assessmentreport in response to warn of the increased risk level. The alert couldbe delivered electronically by email, text message, social media, orother electronic communication, or delivered by physical media such asthe postal service. The alert could be delivered to the subject personor to a person associated with the subject person, such as a doctor,spouse, parent or companion of the subject person. Data points 5 and 6show a reduced rate of ultraviolet light exposure towards the end of thefirst year. The reduced rate of exposure may have been a change inbehavior of the subject person in response to the alert of data point 4,in response to a change in seasons, or any other of a number of reasons.

In the second year of the example of FIG. 11, the subject person startsthe year with a low ultraviolet light exposure rate at data point 7,such as the person of FIG. 2. Data points 8, 10, 11 and 12 show a mediumrisk of ultraviolet light exposure, such as the person of FIG. 3 andFIG. 4. Data point 9 shows a very high level of ultraviolet lightexposure and likely may likely be the result of a sunburn, such as theperson of FIG. 5. Line 1122 is a graphical representation of an averageexposure of ultraviolet light for the second year of the graph basedupon the data points 7-12. The average is more than two hours per dayand less than four hours per day, thus the ultraviolet light exposurerisk is medium. The health assessment report would then show that in thesecond year of the assessment the ultraviolet risk was medium. Datapoint 9 resulted in a determined exposure beyond four hours per dayresulting in a determined high risk for the subject person. If thesocial media data was analysed at a point in time close to theoccurrence of data point 9, then in response a health assessment reportalert could be generated to warn of the high risk level. Similar to thediscussion of data point 4, warning alerts can be generated for datapoints 8, 10, 11 and 12. Line 1130 shows the seasonal peak ultravioletlight exposure (excluding sunburn data point 9, which may be consideredan exception in ultraviolet light exposure in the trend of the secondyear) increasing between the first and second years. The healthassessment report may reflect that a finding that the seasonal peakexposure has increased as shown by line 1130 and is resulting in amedium level of risk. The health assessment report of the ultravioletlight exposure profile of line 1100 may also note a seasonal variationin that seasonally, the minimum exposure of data points 1, 2 and 5, 6, 7appears a low risk from year to year, the peak exposure of data points3, 4 and 8, 10, 11 show an increasing peak exposure on a seasonal basis.The health assessment report may also determine the ultraviolet lightexposure risk over the duration of the ultraviolet light exposureprofile, which in the example of FIG. 11 is two years, in other examplesthe duration may be shorter or significantly longer than two years, andmay be for the lifetime of the subject person, depending on the datamined from the social media databases.

The health assessment report may be used to the benefit of the subjectperson in reducing the risks associated with ultraviolet light exposure.The health assessment report may go further to estimate a risk level forthe subject person for certain cancers, including at least one ofmelanoma, basal cell carcinoma and squamous cell carcinoma, as well asother disorders related to ultraviolet light exposure and may be usedfor providing advice for the modification of behaviors to mitigate suchrisks. In arriving at the estimation, the health assessment report mayweigh at least one additional factor including individual attributesincluding, moles, freckling, skin lesions, hair colour, family historyof melanoma, personal history of melanoma, age, gender, xerodermapigmentosum, history of indoor tanning, and eye colour of the subjectperson. Since the ultraviolet light exposure profile is mined fromsocial media databases, the profile for each individual may bedetermined over a very long period of time with numerous data points,thereby increasing the accuracy of the health assessment report withlittle investment in time by the subject person in the gathering and/orprovisioning of data for the report. When adopted on a large scale, thehealth assessment report for a larger segment of the population can helpreduce the significant burdens skin cancer and related abnormalitiesplaces upon the health of the population.

FIG. 12 illustrates an example of a representative flow diagram of aprocess for generating a health assessment report for a subject personbased upon an ultraviolet light exposure profile analysed from amultiplicity of data points received from social media databases. Step1202 receives data from a remote social media database and step 1204determines if the data includes an image related to the subject person.The image may include the subject person or may include an image of aperson related to a subject person. If so, step 1210 then determines theultraviolet light exposure level of the subject person from the image,and step 1214 determines a time of the image recording. The time ofimage recording may be determined by a timestamp in metadata associatedwith the image or may be included in other data from the social mediadatabase. If the data does not include an image related to the subjectperson in step 1204, then step 1216 determines if the data indicates anactivity indicative of ultraviolet light exposure of the subject person,as previously described. If so, step 1218 then determines theultraviolet light exposure level of the subject person based upon theactivity and step 1220 determines the time of the activity. An exampleof such an activity may be a calendar appointment showing an activitythat may involve exposure to ultraviolet light. Then from either steps1204, 1216 or 1220, step 1222 determines if more data is available fromthe currently selected social media database. If more data is available,then step 1224 selects the next data and returns to step 1202. If thecurrently selected social media database is mined, then step 1226determines if another social media database should be examined, and ifso selects the next social media database at step 1228 selects the firstdata portion of the next social media database and returns to step 1202.If all databases have been examined, then step 1226 proceeds to step1230 to generate an ultraviolet light exposure profile. FIG. 11 shows anexample of at least a portion of an ultraviolet light exposure profile.Then step 1232 generates health assessment report based upon theultraviolet light exposure profile and if an exposure threshold isexceeded, an alert may be generated. The health assessment report mayinclude analysis of a risk of skin cancer of the selected person as wellas advise of certain behaviors that may be beneficial or detrimentalbased upon data minded from social media databases. The alert mayinclude a timely notice of a substantial risk of over exposure toultraviolet light.

FIG. 13 illustrates an example of a representative flow diagram of aprocess for determining ultraviolet light exposure of a subject personfrom an image. FIG. 13 corresponds to an example of a more detaileddescription of the process of step 1210 of FIG. 12. Step 1300 determinesif facial recognition and/or metadata indicates the subject person isincluded in the image that was received from the social media databasethat is currently being analysed. If so, step 1302 determines theportion of the image including a skin characteristic of the subjectperson for analysis. The portion of skin may be any portion, for examplemay include the forehead of the subject person. Then step 1304determines the ultraviolet light exposure based upon the selected imageportion, which may include using the graph of FIG. 6 to relate skincolour to an ultraviolet light exposure level. If the subject person isnot included in the image at step 1302, then step 1306 determines if aperson related to the subject person is included in the image. Therelated person may include a spouse, friend or companion of the subjectperson. The presence of the related person in the image may bedetermined by analysing metadata associated with the image, or byperforming facial recognition on the image to determine if the face ofthe related person is included in the image or other process fordetermining a relationship with the subject person. Otherwise step 1308determines if the image was recorded with a camera associated with thesubject person, if so step 1310 designates a person in the image as arelated person. Step 1314 determines an image portion including a skincharacteristic of the related person and step 1316 determines theultraviolet light exposure of the subject person based upon theultraviolet light exposure of the related person included in the image.Otherwise, step 1318 may use other processes to determine ultravioletlight exposure from the image. For example the image may be one of aseries of sunny images of an outdoor tennis match, for example, taken bya camera associated with the subject person. In response, it may bedetermined that the subject person received ultraviolet light exposurefor the duration of the series of photographs. Another example would beto analyse changes in hair colour, freckling or skin blemishes todetermine ultraviolet light exposure.

FIG. 14 illustrates an example of a representative flow diagram of aprocess for determining ultraviolet light exposure by analysing skincolour included within an image. The skin colour may be that of thesubject person or a person related to the subject person. The flowdiagram enters at step 1400 and step 1402 determines if attributes of aperson included in the image portion are known or ascertainable and ifso, step 1404 determines the ultraviolet light exposure based upon theskin colour. FIG. 6 represents a graph for determining an ultravioletlight exposure level of person with known attributes based upon skincolour. The person may be the subject person or a related person. Theattributes may be already determined or ascertainable using data fromsocial media databases and include age, gender, hair colour, eye colour,skin type, and geographic origin. If the attributes are not known, step1406 determines if a light skin colour and a dark skin colourcharacteristic are included in the image, similar to the example imageof FIG. 8. If so, step 1408 determines ultraviolet light exposure basedupon the dark and light skin colour characteristics as previouslydescribed with respect to FIG. 8. Otherwise, step 1410 determines if atleast one other image of the person included in the image portion isavailable. If so, then the images are compared in step 1412 and thechanges in skin characteristics including skin colour, freckling, and/orblemishes are analysed in step 1404 to determine ultraviolet lightexposure in step 1416. For example, if one photo has a person with askin colour corresponding to light skin colour of area 830 of FIG. 8 andanother photo has the person with a skin colour corresponding to thedark area 820 of FIG. 8, then the graph of FIG. 6 may be used todetermine ultraviolet light exposure level for the image of the personwith a skin colour corresponding to the darker area. Otherwise, otherapproaches may be used to analyse skin characteristics to determineultraviolet light exposure in step 1418 while remaining within the scopeof this description.

The respective implementations of the present disclosure can be carriedout in any appropriate mode, including hardware, software, or firmwarestored on a storage media and executed computer storage program product,or combination thereof. Alternatively, it is possible to at leastpartially carry out the implementation of the present disclosure ascomputer software executed on one or more data processors and/or adigital signal processor. The components and modules or processes of theimplementation of the present disclosure can be implemented physically,functionally and logically in any suitable manner. Indeed, the functioncan be realized in a single member or in a plurality of members, or as apart of other functional members. Thus, it is possible to implement theimplementation of the present disclosure in a single member ordistribute it physically and functionally between different members anda processor.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present disclosure are described herein with reference toflowchart illustrations flow diagrams and/or block diagrams of methods,apparatus (systems) and computer program products according toimplementations of the disclosure. It will be understood that each blockof the flowchart illustrations and/or block diagrams, and combinationsof blocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe blocks of the flowchart illustrations and/or block diagrams.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer or other programmable dataprocessing apparatus to function in a particular manner, such that theinstructions stored in the computer readable medium produce an articleof manufacture including instruction means which implement thefunctions/acts specified in the blocks of the flowchart illustrationsand/or block diagrams.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmabledata processing apparatus to produce a computer implemented process suchthat the instructions which execute on the computer or otherprogrammable apparatus provide processes for implementing thefunctions/acts specified in the blocks of the flowchart illustrationsand/or block diagrams.

The present disclosure is described by use of detailed illustration ofthe implementations of the present disclosure, and these implementationsare provided as examples and do not intend to limit the scope of thepresent disclosure. Although these implementations are described in thepresent disclosure, modifications and variations on theseimplementations will be apparent to those of ordinary skill in the art.Therefore, the above illustration of the exemplary implementations doesnot confine or restrict the present disclosure. Other changes,substitutions and modifications are also possible, without departingfrom the scope of the description and the appended claims.

What is claimed is:
 1. A method comprising: receiving a multiplicity of images from an at least one remote database; analysing, by a digital processing machine, the multiplicity of images to determine an ultraviolet light exposure profile of a subject person; and generating a health assessment report for the subject person based upon the ultraviolet light exposure profile, wherein a related person having a relationship with the subject person has a related skin characteristic that varies based upon exposure to ultraviolet light, and the analysing further includes: determining a presence of the related person within the multiplicity of images; determining the related skin characteristic of the related person for each of the multiplicity of images; and determining an ultraviolet light exposure level for the related person, and the determining the ultraviolet profile of the subject person further includes determining the ultraviolet profile of the subject person based upon the ultraviolet light exposure level of the related person.
 2. The method according to claim 1 wherein the receiving further includes receiving a first plurality of the multiplicity of images from a first remote database including a first social media database; and receiving a second plurality of the multiplicity of images from a second remote database including a second social media database different from the first social media database.
 3. The method according to claim 1 wherein the subject has a skin characteristic that varies based upon exposure to ultraviolet light, and the receiving further receives metadata associated with the multiplicity of images, the metadata including a timestamp associated with each of the multiplicity of images indicative of a time of image recording, and the analysing further includes determining a presence of the subject person within a plurality of images of the multiplicity of images, and determining the skin characteristic of the subject person in each of the plurality of images in which the subject person is present, and the generating generates the health assessment report based upon the skin characteristic and the timestamp from each of the plurality of images in which the subject person is present.
 4. The method according to claim 3 wherein the skin characteristic includes at least one of skin colour, skin freckling, skin blemishes and skin lesions.
 5. The method according to claim 3 wherein the skin characteristic includes skin colour and the analysing determines the ultraviolet profile based upon at least one individual attribute associated with the subject person and the skin colour, the at least one individual attribute indicative of a relationship between skin colour and exposure to ultraviolet light of the subject person, the individual attribute including at least one of age, gender, hair colour, eye colour, skin type, and geographic origin.
 6. The method according to claim 3 wherein the skin characteristic includes skin colour and the multiplicity of images includes an image of the subject person having an exposed area of skin having exposure to ultraviolet light and an unexposed area of skin having less exposure to ultraviolet light than the exposed area of skin and the analysing further includes determining a first skin colour of the exposed area of skin, determining a second skin colour of the unexposed area of skin, and determining the ultraviolet profile includes determining the ultraviolet profile based upon the first skin colour and the second skin colour.
 7. The method according to claim 3 wherein the subject person has a hair colour that varies based upon exposure to ultraviolet light, and the analysing further includes determining the hair colour of the subject person for each of the plurality of images in which the subject person is present, and the generating generates the health assessment report further based upon the hair colour and the timestamp of each of the plurality of images in which the subject person is present.
 8. The method according to claim 3 wherein the generating further generates the health assessment report based upon at least one additional factor including moles, freckling, hair colour, family history of melanoma, personal history of melanoma, age, gender, xeroderma pigmentosum, history of indoor tanning, and eye colour of the subject person.
 9. The method according to claim 3 wherein the metadata includes information indicative of a behavior of the subject person, the behavior of the subject person is indicative of exposure to ultraviolet light and the analysing further analyses the metadata to determine the behavior of the subject person in determining the ultraviolet light exposure profile of the subject person.
 10. The method according to claim 9 wherein the behavior of the subject person includes at least one of a vacation location, participation in an outdoor sport, an ultraviolet tanning salon visit, and a chemical spray tanning salon visit.
 11. The method according to claim 3 wherein the skin characteristic varies on a seasonal basis with a potential for an increased ultraviolet light exposure during a first season and a decreased ultraviolet light exposure during a second season and further wherein the analysing determines the ultraviolet light exposure profile based upon seasonal variation of the skin characteristic.
 12. The method according to claim 1 wherein the health assessment report includes determining a risk level of a skin cancer, the skin cancer including at least one of melanoma, basal cell carcinoma and squamous cell carcinoma.
 13. The method according to claim 12 further comprising the step of generating an alert based upon the risk level exceeding a threshold.
 14. A computer storage program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit configured to perform a method comprising: receiving a multiplicity of images from an at least one remote database; analysing the multiplicity of images to determine an ultraviolet light exposure profile of a subject person; and generating a health assessment report for the subject person based upon the ultraviolet light exposure profile, wherein a related person having a relationship with the subject person has a related skin characteristic that varies based upon exposure to ultraviolet light, and the analysing further includes: determining a presence of the related person within the multiplicity of images; determining the related skin characteristic of the related person for each of the multiplicity of images; and determining an ultraviolet light exposure level for the related person, and the determining the ultraviolet profile of the subject person further includes determining the ultraviolet profile of the subject person based upon the ultraviolet light exposure level of the related person.
 15. The computer storage program product according to claim 14 wherein the subject has a skin characteristic that varies based upon exposure to ultraviolet light, and the receiving further receives metadata associated with the multiplicity of images, the metadata including a timestamp associated with each of the multiplicity of images indicative of a time of image recording, and the analysing further includes determining a presence of the subject person within a plurality of images of the multiplicity of images, and determining the skin characteristic of the subject person in each of the plurality of images in which the subject person is present, and the generating generates the health assessment report based upon the skin characteristic and the timestamp from in each of the plurality of images in which the subject person is present.
 16. The computer storage program product according to claim 15 wherein the skin characteristic includes skin colour and the multiplicity of images includes an image of the subject person having an exposed area of skin having exposure to ultraviolet light and an unexposed area of skin having less exposure to ultraviolet light than the exposed area of skin and the analysing further includes determining a first skin colour of the exposed area of skin, determining a second skin colour of the unexposed area of skin, and determining the ultraviolet profile includes determining the ultraviolet profile based upon the first skin colour and the second skin colour.
 17. The computer storage program product according to claim 15 wherein a related person having a relationship with the subject person has a related skin characteristic that varies based upon exposure to ultraviolet light, and the analysing further includes: determining a presence of the related person within the multiplicity of images; determining the related skin characteristic of the related person for each of the multiplicity of images; and determining an ultraviolet light exposure level for the related person, and determining the ultraviolet profile of the subject person further includes determining the ultraviolet profile of the subject person based upon the ultraviolet light exposure level of the related person.
 18. A device comprising: a data receiver configured to receive a multiplicity of images recorded with visible light, the multiplicity of images received from a plurality of social media databases; a subject person identifier configured to analyse the multiplicity of images to identify a plurality of subject person images including a subject person having a skin colour that varies with exposure to ultraviolet light; a skin colour determiner configured to determine a skin colour of the subject person within each of the subject person images; an ultraviolet light exposure determiner configured to generate a multiplicity of data points corresponding to the multiplicity of images, each data point corresponding to an ultraviolet light exposure level for each of the subject person images determined based upon the skin colour of the subject person within each of the subject person images; a multiple photo analyser configured to generate an ultraviolet light exposure profile for the subject person based upon the multiplicity of data points; and a report generator configured to generate a health assessment report for the subject person based upon the ultraviolet light exposure profile, the health assessment report including an ultraviolet light exposure risk assessment for the subject person.
 19. The device according to claim 18 wherein a related person having a relationship with the subject person has a related skin colour that varies based upon exposure to ultraviolet light, and further wherein the subject person identifier is further configured analyse the multiplicity of images to identify an at least one related person image including the related person, the skin colour determiner configured to determine a skin colour of the related person within at least one related person image, and the ultraviolet light exposure determiner is further configured to generate at least one of the multiplicity of data points corresponding to an ultraviolet light exposure level of the at least one related person image determined based upon the skin colour of the related person within the at least one related person image, wherein the health assessment report includes the ultraviolet light exposure risk assessment for the subject person based at least in part upon the determined ultraviolet light exposure level of the related person. 